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      Comparison of the Schwartz and CKD-EPI Equations for Estimating Glomerular Filtration Rate in Children, Adolescents, and Adults: A Retrospective Cross-Sectional Study

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          Abstract

          Background

          Estimating kidney glomerular filtration rate (GFR) is of utmost importance in many clinical conditions. However, very few studies have evaluated the performance of GFR estimating equations over all ages and degrees of kidney impairment. We evaluated the reliability of two major equations for GFR estimation, the CKD-EPI and Schwartz equations, with urinary clearance of inulin as gold standard.

          Methods and Findings

          The study included 10,610 participants referred to the Renal and Metabolic Function Exploration Unit of Edouard Herriot Hospital (Lyon, France). GFR was measured by urinary inulin clearance (only first measurement kept for analysis) then estimated with isotope dilution mass spectrometry (IDMS)–traceable CKD-EPI and Schwartz equations. The participants’ ages ranged from 3 to 90 y, and the measured GFRs from 3 to 160 ml/min/1.73 m 2. A linear mixed-effects model was used to model the bias (mean ratio of estimated GFR to measured GFR). Equation reliability was also assessed using precision (interquartile range [IQR] of the ratio) and accuracy (percentage of estimated GFRs within the 10% [P10] and 30% [P30] limits above and below the measured GFR). In the whole sample, the mean ratio with the CKD-EPI equation was significantly higher than that with the Schwartz equation (1.17 [95% CI 1.16; 1.18] versus 1.08 [95% CI 1.07; 1.09], p < 0.001, t-test). At GFR values of 60–89 ml/min/1.73 m 2, the mean ratios with the Schwartz equation were closer to 1 than the mean ratios with the CKD-EPI equation whatever the age class (1.02 [95% CI 1.01; 1.03] versus 1.15 [95% CI 1.13; 1.16], p < 0.001, t-test). In young adults (18–40 y), the Schwartz equation had a better precision and was also more accurate than the CKD-EPI equation at GFR values under 60 ml/min/1.73 m 2 (IQR: 0.32 [95% CI 0.28; 0.33] versus 0.40 [95% CI 0.36; 0.44]; P30: 81.4 [95% CI 78.1; 84.7] versus 63.8 [95% CI 59.7; 68.0]) and also at GFR values of 60–89 ml/min/1.73 m 2. In all patients aged ≥65 y, the CKD-EPI equation performed better than the Schwartz equation (IQR: 0.33 [95% CI 0.31; 0.34] versus 0.40 [95% CI 0.38; 0.41]; P30: 77.6 [95% CI 75.7; 79.5] versus 67.5 [95% CI 65.4; 69.7], respectively). In children and adolescents (2–17 y), the Schwartz equation was superior to the CKD-EPI equation (IQR: 0.23 [95% CI 0.21; 0.24] versus 0.33 [95% CI 0.31; 0.34]; P30: 88.6 [95% CI 86.7; 90.4] versus 29.4 [95% CI 26.8; 32.0]). This study is limited by its retrospective design, single-center setting with few non-white patients, and small number of patients with severe chronic kidney disease.

          Conclusions

          The results from this study suggest that the Schwartz equation may be more reliable than the CKD-EPI equation for estimating GFR in children and adolescents and in adults with mild to moderate kidney impairment up to age 40 y.

          Abstract

          In this retrospective cross-sectional study, Luciano da Silva Selistre and colleagues compare Schwartz and CDK-EPI equations for estimating glomerular filtration rate in patients of different ages and degrees of renal impairment.

          Editors' Summary

          Background

          Throughout life, our kidneys filter waste products (from food and from the normal breakdown of tissues) and excess water from our blood to make urine. If our kidneys stop working for any reason, the rate at which they filter the blood (the glomerular filtration rate, or GFR) decreases, and dangerous amounts of creatinine and other waste products build up in the blood. Kidneys can stop working suddenly, but in chronic kidney disease (CKD), a condition that affects more than 10% of the world’s population, kidney function declines gradually over many years. The symptoms of CKD, which rarely occur until the disease is very advanced, include tiredness, swollen feet, and frequent urination, especially at night. CKD cannot be cured, but its progression can be slowed by controlling high blood pressure and diabetes and by adopting a healthy lifestyle; the same interventions also reduce the chance of CKD developing in the first place.

          Why Was This Study Done?

          CKD is linked with an increased risk of end-stage renal (kidney) disease and cardiovascular disease. Early identification of CKD can prevent these life-threatening complications, so clinical practice guidelines have been proposed for the diagnosis and management of CKD in the general population. The assessment of GFR is central to these guidelines. GFR can be measured by infusing inulin, a compound that is eliminated from the body by glomerular filtration, into the blood and measuring its rate of appearance in the urine. However, in routine clinical practice, GFR is usually estimated from blood creatinine levels using a GFR estimating equation (creatinine levels vary considerably within and between individuals, so an equation is needed to convert measured creatinine levels into GFR estimates). Examples of creatinine-based GFR estimation equations include the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation and the Schwartz equation, which were developed in middle-aged adults and children, respectively. Few studies have evaluated the performance of such equations over all ages and levels of kidney impairment, so here the researchers assess the reliability of the CKD-EPI and Schwartz equations for estimating GFR in children, adolescents, and adults.

          What Did the Researchers Do and Find?

          In 10,610 individuals referred to a single French hospital because of suspected or established kidney disease or before kidney donation, the researchers compared GFR measured by inulin clearance with GFR estimated using the CKD-EPI and Schwartz equations. They evaluated the reliability of each equation by calculating the average (mean) ratio of estimated GFR to measured GFR (a ratio of 1 indicates that the equation yielded GFR values identical to those from the gold-standard inulin clearance test) and by assessing the precision and accuracy of the estimated GFR values: the precision of a measurement indicates its reproducibility and reliability; the accuracy of a measurement indicates its closeness to the true value of a quantity. Across all the participants, the mean ratio of estimated GFR to measured GFR with the Schwartz equation was nearer to 1 than the mean ratio for the CKD-EPI equation. Among participants of all ages with measured GFR values indicating mild loss of kidney function, the mean ratio obtained with Schwartz equation was also nearer to 1 than that obtained with the CKD-EPI equation. Among young adults (18–40 years old) with measured GFR values indicating mild to moderate loss of kidney function, the Schwartz equation had better precision and was more accurate than the CKD-EPI equation, but, in all patients aged ≥65 years, the CKD-EPI equation performed better than the Schwartz equation. Finally, in children and adolescents, the Schwartz equation performed better than the CKD-EPI equation.

          What Do These Findings Mean?

          Several aspects of this study (for example, its single-site setting and the low numbers of participants with severe CKD) may limit the accuracy and generalizability of its findings. However, these findings suggest that the Schwartz equation may be more reliable than the CKD-EPI equation for estimating GFR in children and adolescents and in adults up to 40 years old with mild to moderate kidney impairment. Up to now, there has been no consensus about when physicians should switch from using the Schwartz equation (which was developed in children) to using the CKD-EPI equation (which was developed in middle-aged adults) to estimate GFR in their patients. The findings of this study might therefore help physicians decide when to make this switch, thereby improving clinical decision-making and possibly helping to reduce the global burden of CKD.

          Additional Information

          This list of resources contains links that can be accessed when viewing the PDF on a device or via the online version of the article at http://dx.doi.org/10.1371/journal.pmed.1001979.

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          Most cited references13

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          Evaluation of the Chronic Kidney Disease Epidemiology Collaboration equation for estimating the glomerular filtration rate in multiple ethnicities.

          An equation from the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) provides more accurate estimates of the glomerular filtration rate (eGFR) than that from the modification of diet in renal disease (MDRD) Study, although both include a two-level variable for race (Black and White and other). Since creatinine generation differs among ethnic groups, it is possible that a multilevel ethnic variable would allow more accurate estimates across all groups. To evaluate this, we developed an equation to calculate eGFR that includes a four-level race variable (Black, Asian, Native American and Hispanic, and White and other) using a database of 8254 patients pooled from 10 studies. This equation was then validated in 4014 patients using 17 additional studies from the United States and Europe (validation database), and in 1022 patients from China (675), Japan (248), and South Africa (99). Coefficients for the Black, Asian, and Native American and Hispanic groups resulted in 15, 5, and 1% higher levels of eGFR, respectively, compared with the White and other group. In the validation database, the two-level race equation had minimal bias in Black, Native American and Hispanic, and White and other cohorts. The four-level ethnicity equation significantly improved bias in Asians of the validation data set and in Chinese. Both equations had a large bias in Japanese and South African patients. Thus, heterogeneity in performance among the ethnic and geographic groups precludes use of the four-level race equation. The CKD-EPI two-level race equation can be used in the United States and Europe across a wide range of ethnicity.
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            • Article: not found

            Comparative performance of the CKD Epidemiology Collaboration (CKD-EPI) and the Modification of Diet in Renal Disease (MDRD) Study equations for estimating GFR levels above 60 mL/min/1.73 m2.

            The Modification of Diet in Renal Disease (MDRD) Study equation underestimates measured glomerular filtration rate (GFR) at levels>60 mL/min/1.73 m2, with variable accuracy among subgroups; consequently, estimated GFR (eGFR)>or=60 mL/min/1.73 m2 is not reported by clinical laboratories. Here, performance of a more accurate GFR-estimating equation, the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, is reported by level of GFR and clinical characteristics. Test of diagnostic accuracy. Pooled data set of 3,896 people from 16 studies with measured GFR (not used for the development of either equation). Subgroups were defined by eGFR, age, sex, race, diabetes, prior solid-organ transplant, and body mass index. eGFR from the CKD-EPI and MDRD Study equations and standardized serum creatinine. Measured GFR using urinary or plasma clearance of exogenous filtration markers. Mean measured GFR was 68+/-36 (SD) mL/min/1.73 m2. For eGFR or=90 mL/min/1.73 m2. Limited number of elderly people and racial and ethnic minorities with measured GFR. The CKD-EPI equation is more accurate than the MDRD Study equation overall and across most subgroups. In contrast to the MDRD Study equation, eGFR>or=60 mL/min/1.73 m2 can be reported using the CKD-EPI equation. Copyright (c) 2010 National Kidney Foundation, Inc. All rights reserved.
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              • Article: not found

              Kidney dimensions at sonography: correlation with age, sex, and habitus in 665 adult volunteers.

              The purpose of this study was to investigate the normal sonographic measurements of the kidney in adult volunteers. Length, width, and thickness of the kidney and its central echogenic area and the parenchymal thickness of the upper pole were measured in an age- and sex-stratified random sample of 665 volunteers 30, 40, 50, 60, and 70 years old. Measurements were made with the volunteers prone. Volumes of the kidney, the central echogenic area, and the renal parenchyma were calculated. Renal dimensions and renal and parenchymal volume were correlated with age, height, weight, body mass index, and total body area. In 94 subjects, renal length was measured with the volunteers supine also. Median renal lengths were 11.2 cm on the left side and 10.9 cm on the right side. Median renal volumes were 146 cm3 in the left kidney and 134 cm3 in the right kidney. Renal size decreased with age, almost entirely because of parenchymal reduction. Renal volume correlated best with total body area. Renal length correlated best with body height. Measurements of renal length obtained with the subjects supine were not significantly different from those obtained with the subjects prone. The most exact measurement of renal size is renal volume, which showed the strongest correlation with height, weight, and total body area. Clinically, measurement of renal length is most practical and can be done with the subject prone or supine.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                29 March 2016
                March 2016
                : 13
                : 3
                : e1001979
                Affiliations
                [1 ]Exploration Fonctionnelle Rénale et Métabolique, Groupement Hospitalier Est Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
                [2 ]Coordenação de Aperfeiçoamento do Pessoal de Nível Superior (CAPES), Brasilia, Brazil
                [3 ]Programa de Pós-graduação em Medicina e Ciências da Saúde, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil
                [4 ]Programa de Pós-graduação em Ciências da Saúde, Universidade de Caxias do Sul, Caxias do Sul, Brazil
                [5 ]Service de Biostatistique, Hospices Civils de Lyon, Lyon, France
                [6 ]Université de Lyon, Lyon, France
                [7 ]CNRS UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique-Santé, Villeurbanne, France
                [8 ]UMR 5305, Biologie Tissulaire et Ingénierie Thérapeutique, Université Claude Bernard, Lyon, France
                [9 ]Centre de Référence des Maladies Rénales Rares, Service de Néphrologie et Rhumatologie Pédiatriques, Hospices Civils de Lyon, Lyon, France
                [10 ]INSERM UMR 1060, Université Claude Bernard Lyon I, Lyon, France
                [11 ]Laboratoire de Biochimie et Biologie Moléculaire, Groupement Hospitalier Est Hôpital Edouard Herriot, Hospices Civils de Lyon, Lyon, France
                Instituto Mario Negri, ITALY
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: LS MR PC LD. Performed the experiments: SL LD. Analyzed the data: LS MR. Contributed reagents/materials/analysis tools: LS MR PC VS JI SL FB CPF LD. Wrote the first draft of the manuscript: LS MR PC VS JI SL FB CPF LD. Contributed to the writing of the manuscript: LS MR PC VS JI SL FB CPF LD. Enrolled patients: LS LD. Agree with the manuscript’s results and conclusions: LS MR PC VS JI SL FB CPF LD. All authors have read, and confirm that they meet, ICMJE criteria for authorship.

                Article
                PMEDICINE-D-15-01238
                10.1371/journal.pmed.1001979
                4811544
                27023756
                f80b5d34-d977-4692-9af5-9d73b29ad47e
                © 2016 Selistre et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 April 2015
                : 9 February 2016
                Page count
                Figures: 3, Tables: 5, Pages: 18
                Funding
                The study was funded by CAPES foundation Ministry of Education of Brazil and Laboratoire Biostatistique Santé (Université de Lyon 1 -CNRS 5558).
                Categories
                Research Article
                Biology and Life Sciences
                Physiology
                Renal Physiology
                Glomerular Filtration Rate
                Medicine and Health Sciences
                Physiology
                Renal Physiology
                Glomerular Filtration Rate
                Biology and Life Sciences
                Anatomy
                Renal System
                Kidneys
                Medicine and Health Sciences
                Anatomy
                Renal System
                Kidneys
                Medicine and Health Sciences
                Nephrology
                Chronic Kidney Disease
                People and Places
                Population Groupings
                Age Groups
                Adolescents
                People and Places
                Population Groupings
                Age Groups
                Adults
                People and Places
                Population Groupings
                Age Groups
                Young Adults
                Biology and Life Sciences
                Anatomy
                Body Fluids
                Urine
                Medicine and Health Sciences
                Anatomy
                Body Fluids
                Urine
                Biology and Life Sciences
                Physiology
                Body Fluids
                Urine
                Medicine and Health Sciences
                Physiology
                Body Fluids
                Urine
                Biology and Life Sciences
                Biochemistry
                Biomarkers
                Creatinine
                Custom metadata
                Data can be accessed through dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/SKSPSY.

                Medicine
                Medicine

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